Consider a community of users who share digital content through their handheld devices. If there are many such users, and no (or a very poor) means of filtering, they may suffer from content overload. To avoid this, it would be preferable if users could effectively select content that both lies within their range of interests and comes from sources that are trustworthy. Users may do so by running trust models on their devices. A trust model is a piece of software that keeps track of which devices are trusted and which are not.
This talk will look at how a trust model running on device A determines the extent to which A should initially trust device B in a given context (content category). It does so by considering two cases: in the first, A does not know B at all; in the second case, A knows B but in contexts other than that of interest. For each of those two cases, this talk will discuss the most recent proposal that improves on existing solutions (TRULLO and distributed propagation), and will also attempt to suggest new research directions (such as private collaborative filtering – post & more).